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At present, China’s forestry development is mainly driven by the traditional production factors such as forestry labor force, land resources and capital and thus the top priority of forestry development is to optimize forestry production factors. Scientific and effective forestry labor input has a significant role in promoting the development of forestry industry. Given that the actual input to forestry labor is not clear, the accuracy of the forestry industry development may be slightly affected. Based on the monitoring project of collective forest tenure reform (RCFT), this paper uses the survey data of 3,500 rural households in seven provinces of China from 2010 to 2014 and 2016 to 2017 to measure the actual labor force in China, and empirically analyzes and studies the factors influencing the development of forestry industry based on the provincial data of forestry in China, and further discusses the heterogeneous impact of forestry production factors on the development of forestry industry.

In this paper, the generalized least squares estimation model is used to calculate the actual number of forestry labor in China, and then the Cobb–Douglas production function is selected to explore the influencing factors of forestry industry development.

The results show that the actual number of forestry labor force in China continues to decline and the degree of reduction varies from different regions. The forestry labor is a major factor that promotes the development of the forestry industry, but this promotion is affected by the low matching degree between the forestry production factors and thus further inhibits the development of the forestry industry. Due to the time lag of the reform, the implementation of RCFT first weakens and then promotes the development of forestry production. Further on, the forestry labor input is heterogeneous in land resource endowment, forestry investment source and the proportion of management personnel.

Therefore, researches show that the feasible way to promote the development of forestry industry is to expand the scale of forestry labor force, optimize the mutual allocation of forestry production factors, enhance the input of human capital in forestry and deepen the RCFT.

Digital transformation is a confidence booster in intrapreneurship, but few have examined its impact on intrapreneurship. Further, quantitative analyses exploring the impact of Chinese enterprises' digital transformation on intrapreneurship at the micro-level are rare. Most enterprises do not have the dividend for digital transformation, and few enterprises have successfully achieved digital transformation through intrapreneurship, internal management re-engineering and technological innovation. This study investigates the effect of digital transformation on intrapreneurship in Chinese real economy enterprises.

The study develops and tests a theoretical model that digital transformation impacts intrapreneurship by promoting working capital turnover and furtherly influencing labor input. Panel data of 1,638 Chinese-listed companies between 2007 and 2020 were used to complete the empirical test.

Digital transformation impacted labor input, with an inverted-U shaped relationship between the two, and labor input significantly stimulated intrapreneurship. This effect promoted labor input's impact on working capital. Chinese real economy enterprises generally increase labor investment to promote intrapreneurship. Heterogeneity analysis revealed that enterprises' asset scale and ownership attributes uniformly affected labor input.

This study provided empirical evidence of the promotional effect of real economy enterprises' digital transformation on intrapreneurship. Further, it advanced the literature by examining this relationship at the micro-level. Moreover, the data sample was long-term and included most industries, thus providing representative results with practical implications.

The purpose of this paper is to identify the effects of recent demographic transition and rising labor costs on agricultural production structure and pattern in China during 1998-2012.

The authors, first, theoretically discuss the effects of changing relative input prices due to rising labor cost on producers’ decisions regarding input mix (substitution effect), output level, and product quality (output effect). A logarithmic mean Divisia index decomposition method is then applied to empirically identify these effects at aggregated levels, followed by an analysis based on the visualization of land use indicators on changing cropping patterns across Chinese provinces.

The authors find that tightened effective agricultural labor supply and rises in rural labor costs are associated with divergent changes in input mixes and output choices across products. Producers of land-intensive products focusing more on input mix adjustment, while those of labor-intensive products seem to more likely to adjust output choices. Producers’ adaption strategies also varied across Chinese provinces due to natural conditions, leading to shifts and concentrations in the regional distribution of agricultural products, with lower-value bulk products concentrating in the plain areas, whereas higher-value horticulture products increasingly prevailing in sloped areas.

This paper illustrates how adjustments in input mixes and output choice in Chinese agriculture counteracted disadvantages caused by rising labor costs and how such adjustments are product and region specific. Based on these observations, implications regarding further innovations in production technology and institutional arrangements needed within China’s agricultural sector are highlighted in the paper.

Economic production analysis can provide critical perspectives on an industry’s performance. The purpose of this paper is to investigate the factor input intensity of hospitality and related industries, namely, accommodation, food service and amusement, gaming and recreation (AFAGR), compared to other service industries.

This paper compared AFAGR with other industries categorized as services by the North American Industry Classification System (NAICS). The NAICS code of up to four digits was used to collect data (US Census Bureau).

Results of this paper confirm extant literature that food service is more labor-intensive than other service industries; however, this was not true of accommodation and AGR industries. Similarly, while food service industry was relatively less intermediate input intensive than other service industries, accommodation and AGR were not. There were no significant differences between hospitality and other service industries (AFAGR) in their capital intensity. Another important finding was that while accommodation had constant results to scale, AGR had increasing returns to scale and food service industry was found to have decreasing returns to scale.

This investigation only looked at the four-digit NAICS-coded industries. International differences could also be investigated in the future.

Based on theoretical arguments, high labor intensity together with low intermediate input in food service industry suggests that efficiencies could be gained in these businesses. This may also be evident by the decreasing returns to scale that this paper found for the food service industry. These comparisons could guide additional research about the causes, consequences and potential sources of improvement of efficiency of economic productivity in AFAGR. Managers in AFAGR would find it valuable to understand how they might be able to enhance economic output, particularly in the context of the role of labor. Furthermore, any changes in one economic input would have implications on other inputs and possibly on productivity.

Any future recalibration of input intensity in hospitality industries could have both social and economic consequence.

This paper enhances our understanding of how hospitality industries use economic factors of production. Labor in AFAGR is viewed as a given. This study suggests that food service industry may need to reevaluate its labor productivity, the way it is measured and how it might affect efficiencies. Such understanding could better inform the sources and causes of economic efficiencies in AFAGR industries. Until now, this understanding has mostly been based on relatively scarce comparative systematic analysis.

The purpose of this paper is to investigate Chinese farmers’ adaptation behavior in the context of the rising cost of labor in agriculture. As the cost of labor increases, farmers will either reallocate their budget to different inputs or change the structure of agricultural production to maximize profit.

The Rural Fixed Point Observation data set between 2004 and 2010 is employed in the empirical analysis of this study. Both the compensated and uncompensated demand elasticities with respect to wages are estimated by adopting the translog cost function and the profit function.

The results show that labor input will drop down significantly as a response to rising wages. Land, fertilizer and intermediate inputs are net complements of labor, whereas machinery appears to be net substitute for labor. In addition, the authors also separate the expansion effect from the substitution effect and find that farmers will shift to grain production with intensive use of fertilizer and from wheat and corn to rice as a response to the rising cost of labor.

This study adopts the classical household model to incorporate various adaptation behaviors of farmers into one framework and decomposes the total effect of the rising cost of labor on input demand into an expansion effect and a substitution effect, which provides a better understanding of farmers’ adaptation behavior.

The relationship between farm size and land productivity is a hotly debated issue in the study of agricultural economics and development economics. The purpose of this paper is to explore the causes leading to the inverse productivity relationship by examining the relationship between farm size and factor inputs.

With a large panel data set of farm households in China during 2010–2011, this study uses the factor demand models to examine the relationship between farm size and per-mu labor and non-labor inputs while employing a stochastic frontier production function in determining the difference of labor efforts in farming operation across farm sizes. Moreover, the models for value-added margins and profits are used to further determine producer behavior of small-size farms.

Results of this study show that, as compared to larger farms, smaller farms not only utilize more labor and non-labor inputs per mu, but also benefit from a higher labor effort. Moreover, smaller farms concentrate more on grain output and cash costs while focusing less on the family labor input costs in an effort to maximize value-added margins rather than profits. The higher yields on smaller farms are thus a result of the utilization of a relatively higher level of labor and non-labor inputs along with skilled-oriented precision farming technology. The inverse productivity relationship is explained by the behavior of small-size producers with employment constraints, leading to smaller farms generating a higher yield than larger farms.

While Sen (1966), Feder (1985), Eswaran and Kotwal (1986) and others have theoretically derived the causal relationship between the incomplete factor markets, especially incomplete labor markets, and the inverse productivity, empirical studies to test the causal relationships are limited. In particular, a solid foundation based on an empirical analysis is lacking when it comes to explaining the inverse productivity in China. Results of this study are expected to have significant policy implications in terms of the understanding of small-size producer behavior and the associated mechanism underlying the inverse relationship between farm size and land productivity.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

This paper revisits the derivation and properties of the Allen-Uzawa and Morishima elasticities. Using a Swiss dataset, this paper empirically estimates various elasticities both in a dual and primal framework using a production theory open economy model and tests for linear homogenous technology. In addition to reporting elasticity at the mean, the standard practice in the literature, this paper also calculates nonparametric distribution of various elasticities. The paper aims to discuss these issues.

To assess the effect of price change on input, the paper estimates a translog cost function and to assess the effect of quantity change on price, the paper estimates the translog distance function using the data on Swiss economy. The paper estimates Allen-Uzawa and Morishima elasticity both under homogenous and non-homogenous technology using the Swiss dataset of one aggregate gross output and four inputs (resident labor, non-resident labor, imports, and capital) over 1950-1986. Elasticities are reported and compared at the mean as well as explored by looking at the range and nonparametric distribution.

This paper shows that constant returns to scale are easily rejected in this dataset and that the elasticities, both qualitatively and quantitatively, are very different under homogenous and non-homogenous technology. These elasticities can switch from complements to substitutes or vice versa when one moves away from the mean of the sample. The equality of the nonparametric elasticity distributions under homogenous vs non-homogenous technology is rejected in all cases except one.

This paper gives a clear derivation and interpretation of different elasticities as well as demonstrates using a dataset how to systematically go about empirically estimating these elasticities in a dual and primal framework. It shows that linear homogenous technology can be easily rejected and the elasticities, both quantitatively and qualitatively, are very different under homogenous and non-homogenous technology. This paper is also very valuable because it shows that the standard practice of reporting elasticity at the mean might not be adequate and there is a possibility that these elasticities can switch from complements to substitutes or vice versa when one moves away from the mean of the sample.

The decline in the share of agriculture in both output and employment is a central feature of structural transformation. The authors present the distinct features between developed and developing countries in the process of agricultural share decline and dig into the real changes that occurred in the agricultural sector during the rapid decline in the agricultural share.

Taking the declining share of agriculture as a clue, the authors depict heterogeneous characteristics in the declining share of agriculture in developed and developing countries. Secondly, by criticizing the factor substitution hypothesis, the authors argue that the essence of agricultural transformation is the process of agricultural industrialization characterized by the combination, reconstruction, and continual changes of agricultural production factors. Finally, based on the theory of agricultural industrialization, this paper analyzes the combination of factors in different stages of declining agricultural share in typical economies.

In this paper, the authors find that the rapid decline in agricultural employment share is accompanied by an increase in the returns to agricultural production in developed economies. In contrast, the decline in agricultural employment share in developing economies lags, and agricultural production efficiency is way much poorer than that of developed economies. Taking the United States and Japan as examples, the authors find that the agricultural sector underwent agricultural industrialization, featured by reconstruction and upgrades of production factors combination.

The authors systematically reveal why huge changes occurred in the agricultural sector in developed economies during structural transformation, and also provide further thoughts and lessons for developing countries to accomplish agricultural modernization.